Test 1

Date, Time, & Location

Monday, February 27, 9:30-10:45am, PM 253

Overview

Test 1 will cover all material from the beginning of the semester through data wrangling (Monday, February 20). The material will cover the assigned readings and the topics we discussed in class.

Format

Multiple Choice
Free Response
CSCI 640 Students will have additional questions

Topics

Python
Relational Algebra
SQL
numpy
pandas
Data (items, attributes, attribute types, semantics, metadata)
Data Wrangling

Readings

Assigned Readings

Wrangler: Interactive Visual Specification of Data Transformation Scripts, S. Kandel et al., 2011
Auto-Transform: Learning-to-Transform by Patterns, Z. Jin et al., 2020

Referenced Papers

Potter’s wheel: An interactive data cleaning system, V. Raman and J. M. Hellerstein, 2001.
Self-Service Data Preparation: Research to Practice, J. M. Hellerstein et al., 2018
Transform-Data-by-Example (TDE): An Extensible Search Engine for Data Transformations, Y. He et al., 2018

Free Response Example Questions

Given a dataset, (a) identify an item, attribute, and cell; (b) state, for each column, whether it is categorical, ordered, or quantitative.
In the following Python code, identify all errors.

    // print the numbers from 1 to 100
    int counter = 1 
    while counter < 100 { 
        print counter 
        counter++
    }

Given the following numpy array, write two different ways to index the highlighted sub-array
State three distinct ways in which Wrangler helps users trying wrangle raw datasets.
Given a data frame, identify issues with the data and how these can be resolved. Exact syntax is not important, explain (and be specific) if you do not recall a particular operation or function name.
How transform data by example (TDE) is different from Wrangler? How does transform by pattern (TBP) improve on transform by example, and what use cases does it aid with?